Морфологическая сегментация

Document retrieval in languages with a rich and complex morphology – par- ticularly in terms of derivation and (single-word) composition – suffers from serious performance degradation with the stemming-only query-term-to-text-word …...

This paper presents some very prelimi- nary results for and problems in develop- ing a statistical machine translation sys- tem from English to Turkish. Starting with a baseline word model …...

Grapheme-to-phoneme conversion (g2p) is a core component of any text-to-speech sys- tem. We show that adding simple syllab- ification and stress assignment constraints, namely ‘one nucleus per syllable’ and ‘one …...

Morphologicalprocesses in Semitic languages deliver space-delimited words which intro- duce multiple, distinct, syntactic units into the structure of the input sentence. These words are in turn highly ambiguous, breaking the …...

For centuries, the deep connection between languages has brought about major discover- ies about human communication. In this pa- per we investigate how this powerful source of information can be …...

Morphological segmentation breaks words into morphemes (the basic semantic units). It is a key component for natural language pro- cessing systems. Unsupervised morphologi- cal segmentation is attractive, because in ev- …...

AbstractThe Arabic language has a very rich morphology where a word is composed of zero or more prefixes, a stem and zero or more suffixes. This makes Arabic data sparse …...

The connection between part-of-speech (POS) categories and morphological properties is well-documented in linguistics but underuti- lized in text processing systems. This pa- per proposes a novel model for morphologi- cal …...

This paper describes an unsupervised dynamic graphical model for morphological segmen- tation and bilingual morpheme alignment for statistical machine translation. The model ex- tends Hidden Semi-Markov chain models by using …...

In this paper, we present an agglomera- tive hierarchical clustering algorithm for labelling morphs. The algorithm aims to capture allomorphs and homophonous morphemes for a deeper analysis of seg- mentation …...

We discuss data-driven morphological segmentation, in which word forms are segmented into morphs, the surface forms of morphemes. Our focus is on a low- resource learning setting, in which only …...

AbstractThis paper introduces a set of freely available, open-source tools for Turkish that are built around TRmorph, a morphological analyzer introduced earlier in Coltekin (2010). The article first provides an …...

Morphological segmentation is an effec- tive sparsity reduction strategy for statis- tical machine translation (SMT) involv- ing morphologically complex languages. When translating into a segmented lan- guage, an extra step …...

We explore the impact of morpholog- ical segmentation on keyword spotting (KWS). Despite potential benefits, state- of-the-art KWS systems do not use mor- phological information. In this paper, we augment …...

We present labeled morphological segmentation—an alternative view of morphological processing that unifies sev- eral tasks. We introduce a new hierarchy of morphotactic tagsets and CHIPMUNK, a discriminative morphological segmen- tation …...

In this paper, we introduce a new approach for joint segmentation, POS tagging and de- pendency parsing. While joint modeling of these tasks addresses the issue of error prop- agation …...

We present a model of morphological seg- mentation that jointly learns to segment and restore orthographic changes, e.g., funniest �→ fun-y-est. We term this form of analysis canon- ical segmentation …...

AbstractUnsupervised learning of morphological segmentation of words in a language, based only on a large corpus of words, is a challenging task. Evaluation of the learned segmentations is a challenge …...

AbstractTo alleviate data sparsity in spoken Uyghur machine translation, we proposed a log-linear based morphological segmentation approach. Instead of learning model only from monolingual annotated corpus, this approach optimizes Uyghur …...

AbstractLearning internal word structure has recently been recognized as an important step in various multilingual processing tasks and in theoretical language comparison. In this paper, we present a neural encoder-decoder …...

AbstractThis paper presents Prompsit Language Engineering’s submission to the IWSLT 2018 Low Resource Machine Translation task. Our submission is based on cross-lingual learning: a multilingual neural machine translation system was …...

AbstractThis paper describes an unsupervised model for morphological segmentation that exploits the notion of paradigms, which are sets of morphological categories (e.g., suffixes) that can be applied to a homogeneous …...

AbstractMorphological segmentation of words is the process of dividing a word into smaller units called morphemes; it is tricky especially when a morphologically rich or polysynthetic language is under question. …...

Nowadays, very little research for Indigenous languages has been studied. Indigenous lan- guages bring significant challenges for Natural Language Processing approaches because of multiple features such as polysynthesis, morphological complexity, …...

AbstractTranslating to and from low-resource polysynthetic languages present numerous challenges for NMT. We present the results of our systems for the English–Inuktitut language pair for the WMT 2020 translation tasks. …...

AbstractThis paper describes a new morphology resource created by Linguistic Data Consortium and the University of Pennsylvania for the DARPA LORELEI Program. The data consists of approximately 2000 tokens annotated …...

AbstractIn cross-lingual language models, representations for many different languages live in the same space. Here, we investigate the linguistic and non-linguistic factors affecting sentence-level alignment in cross-lingual pretrained language models …...

AbstractMorphologically-rich polysynthetic languages present a challenge for NLP systems due to data sparsity, and a common strategy to handle this issue is to apply subword segmentation. We investigate a wide …...

AbstractCommon designs of model evaluation typically focus on monolingual settings, where different models are compared according to their performance on a single data set that is assumed to be representative …...

AbstractTheoretical work in morphological typology offers the possibility of measuring morphological diversity on a continuous scale. However, literature in Natural Language Processing (NLP) typically labels a whole language with a …...

AbstractLanguage modelling and machine translation tasks mostly use subword or character inputs, but syllables are seldom used. Syllables provide shorter sequences than characters, require less-specialised extracting rules than morphemes, and …...

AbstractOur work aims at developing a multilingual data resource for morphological segmentation. We present a survey of 17 existing data resources relevant for segmentation in 32 languages, and analyze diversity …...

AbstractNeural machine translation (NMT) has achieved state-of-art performance in high-resource language pairs, but the performance of NMT drops in low-resource conditions. Morphologically rich languages are yet another challenge in NMT. …...